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. 2025 Feb;197(2):e63907.
doi: 10.1002/ajmg.a.63907. Epub 2024 Oct 15.

KBG Syndrome in 16 Indian Individuals

Shruti Bajaj  1 , Sheela Nampoothiri  2 , Roshni Chugh  1 , Jayesh Sheth  3 , Frenny Sheth  3 , Harsh Sheth  3 , Vinu Narayan  4 , Ameya Deshpande  5 , Anaita Hegde  6 , Aradhana Dwivedi  7 , Dhanya Yeshodharan  2 , Indu Khosla  6 , Madhukar Mittal  8 , Mahesh Kore  9 , Vedam Ramprasad  10 , Anbu Kayalvizhi C  10 , Katta M Girisha  11   12   13
Affiliations

KBG Syndrome in 16 Indian Individuals

Shruti Bajaj et al. Am J Med Genet A. 2025 Feb.

Abstract

We aimed to describe the clinical and genetic characteristics of 16 individuals with KBG syndrome (KBGS) from 13 Indian families. We retrospectively analyzed the clinical details of individuals with KBGS harboring a likely pathogenic/pathogenic variant in ANKRD11. We also analyzed their facial gestalt using Face2Gene and recorded the top three differential disorders suggested by the application. The most frequent clinical features observed in our cohort were as follows: learning and intellectual disability-14/15 (93%), skeletal abnormalities-14/15 (93%), postnatal short stature-13/15 (87%), brachydactyly-11/15 (73%), and characteristic facial appearance-13/15 (87%). We identified 12 single nucleotide variants (SNVs), including six recurrent and six novel variants, and a copy number variant in the 16q24.3 region encompassing ANKRD11 gene. The novel variants were as follows: p.(Gln1236Ter), p.(Asp884ThrfsTer93), p.(Arg1466GlyfsTer87), p.(Tyr2056Ter), p.(Leu955TrpfsTer22), and p.(Lys766ArgfsTer10). The identified SNVs in ANKRD11 clustered around exon 9. We observed a high concordance of Face2Gene in predicting KBGS.

Keywords: artificial intelligence; chromatinopathies; neurodevelopmental disorder; rare disease.

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